3D genome organization links non-coding disease-associated variants to genes

Abstract

Genome sequencing has revealed over 300 million genetic variations in human populations. Over 90% of variants are single nucleotide polymorphisms (SNPs), the remainder include short deletions or insertions, and small numbers of structural variants. Hundreds of thousands of these variants have been associated with specific phenotypic traits and diseases through genome wide association studies which link significant differences in variant frequencies with specific phenotypes among large groups of individuals. Only 5% of disease-associated SNPs are located in gene coding sequences, with the potential to disrupt gene expression or alter of the function of encoded proteins. The remaining 95% of disease-associated SNPs are located in non-coding DNA sequences which make up 98% of the genome. The role of non-coding, disease-associated SNPs, many of which are located at considerable distances from any gene, was at first a mystery until the discovery that gene promoters regularly interact with distal regulatory elements to control gene expression. Disease-associated SNPs are enriched at the millions of gene regulatory elements that are dispersed throughout the non-coding sequences of the genome, suggesting they function as gene regulation variants. Assigning specific regulatory elements to the genes they control is not straightforward since they can be millions of base pairs apart. In this review we describe how understanding 3D genome organization can identify specific interactions between gene promoters and distal regulatory elements and how 3D genomics can link disease-associated SNPs to their target genes. Understanding which gene or genes contribute to a specific disease is the first step in designing rational therapeutic interventions.

Primary osteoarthritis chondrocyte map of chromatin conformation reveals novel candidate effector genes

“…9 These contacts between enhancer and promoter sites can be quantified by chromatin conformation examination techniques like Hi-C, allowing us to link enhancers affected by disease-associated variants to their effector genes. 10 In this study, we aimed to fill a gap in our understanding of osteoarthritis biology by generating the first chromosome conformation map of primary osteoarthritis patient chondrocytes. We leverage the information to glean insights into disease aetiology by linking Hi-C data with publicly available ATAC-seq, 11 ChIP-seq 12 and the latest large-scale osteoarthritis GWAS metaanalysis results.…”

“…The current model of transcriptional activation by enhancers includes binding of several transcription factors, chromatin remodelling proteins and coactivators, to form a mediator complex, which further binds RNA polymerase II at the promoter of the regulated gene, initiating transcription 9. These contacts between enhancer and promoter sites can be quantified by chromatin conformation examination techniques like Hi-C, allowing us to link enhancers affected by disease-associated variants to their effector genes 10…”

Enhancer mutations modulate the severity of chemotherapy-induced myelosuppression

“…The establishment of Capture-C enabled the functional annotation of noncoding GWAS variants (Zhang & Lupski, 2015). With the development of different variations of capture Hi-C technology, most studies are still concentrated on the limited parts of the genome associated with the phenotypes of interest (Orozco et al, 2022). In this article, we performed a non-hypothesis-driven study linking SNVs associated with differing levels of chemotherapy-induced myelosuppression with their target genes at the whole-genome level.…”

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

“…In the context of human disease, HiChIP and similar assays provide a 3D view for the annotation of disease associations of non-coding genetic variants identified from GWAS (Fu et al, 2018; Gazal et al, 2022; Giambartolomei et al, 2021; Orozco et al, 2022; Zhong et al, 2022). Combined with efforts from multiple large consortia for cataloging putative regulatory elements spanning distinct cell types (e.g., ENCODE, BLUEPRINT and Roadmap Epigenomics), mapping such 3D maps of chromatin organization has become a critical piece of the puzzle, which led to formation of the 4D Nucleome Consortium (Dekker et al, 2017; Reiff et al, 2022).…”

“…In the context of human disease, HiChIP and similar assays provide a 3D view for the annotation of disease associations of non-coding genetic variants identified from GWAS (Fu et al, 2018;Gazal et al, 2022;Giambartolomei et al, 2021;Orozco et al, 2022;Zhong et al, 2022).…”